1. Field of the Invention
The present invention relates to a color transforming apparatus used in color image processors such as color copiers and color printers and, in particular, to a method and an apparatus for determining coefficients of color transformation which are used in the above color transforming apparatus. More particularly, the invention concerns a method and an apparatus for determining lattice point data of a look-up table used for color transformation or coefficients of differentiable-continuous function type color transformation.
2. Description of the Related Art
In a color copier, for instance, a color original is read by a color-image input device, the light from the color original is separated into three color components of red, green, and blue, thereby obtaining RGB signals. These RGB signals are transformed into L*a*b* signals. The L*a*b* signals are transformed into YMCK signals corresponding to yellow, magenta, cyan, and black colorants, so as to form a color image on recording paper by a color-image output device.
In the transformation from the L*a*b* signals into YMCK signals, a matrix operation in which a product-sum operation of input signals and color transformation coefficients is performed, or a look-up table is generally used.
The look-up table is a table in which relationships between input values and output values each obtained by multiplying the input values by predetermined color transformation coefficients are stored in advance in a read-only memory (ROM) or a random-access memory (RAM), to effect transformation directly from the L*a*b* signals into YMCK signals. In a case where color transformation is effected by using this look-up table, since an operation time is virtually not required, there is an advantage in that the color transformation can be effected at a very high speed.
The color transformation coefficients for the look-up table are frequently obtained experimentally by trial and error such that the gradation and tone of a color original will be reproduced faithfully when the color original is read by a color-image input device and a reproduced image is actually outputted on recording paper.
Namely, conventionally, there have been cases where estimated values based on a printing or optical model are set as lattice point data of the look-up table on the basis of actually measured values. Incidentally, the lattice point is a point designated by predetermined L*, a*, and b* indicated by an index of the look-up table, and the lattice point data is a post-transformation value corresponding to the lattice point, i.e., the predetermined L*, a*, and b*.
Also, there have been cases where estimated values are obtained by polynomials or other mathematical models.
With respect to output devices, studies in which errors are reduced by modeling input-output characteristics by neural networks are known (e.g., refer to Motohiko Naka, Mie Saito, and Kunio Yoshida: "Color Correction of Color Hard Copy Through Neural Network," Transactions of Study Group of The Institute of Image Electronics Engineers of Japan, 1989). However, no consideration has been given to the use of a neural network in determining the lattice point data of the look-up table.
Generally, in the field of production printing, as shown in FIG. 1B, a plurality of color-image input devices (a drum scanner 1-1, a photo CD 1-2, and a flatbed scanner 1-3) and a plurality of color-image output devices (an image setter 3-1, a color-proofing printer 3-2, and a low-resolution desktop printer 3-3) are generally connected to a host computer 2, and devices are selectively used depending on applications. Since the respective color input-output devices input or output color by means of color signals peculiar to the devices, even if colors are equal, corresponding color signals of the respective devices are not necessarily equal. In such a situation, color matching between an original and an output and color matching between the printed matter for color proofing and the final printed matter are difficult. Accordingly, to overcome this problem, color management systems (CMSs) typified by ColorSync 1.0 by Apple Computer, Inc. and EfiColor by EFI Electronics have come to be used. In these CMSs, attempts have been made to achieve color matching between different devices on the basis of groups of information on device characteristics describing the characteristics of various input-output devices prepared in advance.
However, since the aforementioned CMSs had problems in accuracy and the interchangeability of the groups of information on device characteristics, a method of describing the information on device characteristics has been proposed by Intercolor Consortium (ICC), and has come to be used extensively. According to the ICC's method of describing the information on device characteristics, it is possible to obtain the interchangeability of the groups of information on device characteristics, which has been a drawback of the conventional CMSs.
Since the ICC's method of describing the information on device characteristics is based on a large-scale look-up table and linear interpolations, it is possible to obtain high accuracy as compared with the conventional CMSs.
However, with the above-described models using printing, optics, polynomials, or the like, not only is the estimation error large, but a failure sometimes occurs in color reproduction. In addition, with respect to output devices, in the case of those using neural networks, an input to an output device is estimated from color coordinates such that the error in color signals from the output device is minimized, and the error in a uniform color space of the output result is not minimized. Since the visual perception of humans corresponds to a uniform color space, even if the error in color signals from the output device is merely minimized, the error in visual perception cannot be made sufficiently small.
In addition, in a case where color transformation coefficients are determined by using neural networks, although the accuracy is high, there is a problem in that a very long time and hardware are required for calculation.
Under the present circumstances, since a very large-scale look-up table cannot be easily mounted, mounting is effected in the form of software, or a small-scale look-up table is used. However, the mounting in the form of software presents a problem in the speed of color transformation, and the small-scale look-up table presents a problem in that the accuracy declines.
An ICC profile stores both a table for transforming device-dependent color signals into device-independent signals and a table for transforming device-independent signals into device-dependent signals, but only a table in the forward direction is actually used between them. If a table in the reverse direction is also used jointly at the time of interpolation, it is possible to reduce the interpolation error, but it is difficult to do so in the case of a look-up table in terms of its basic principle. In addition, although high accuracy can be obtained with respect to an independent color transformation, if a plurality of color transformations are synthesized, an interpolating operation becomes necessary. If the color transformation is repeated, there is a problem in that the interpolation errors are accumulated.